<p>We are looking for a senior Data Engineer. This position combines architectural leadership with hands-on development across a modern cloud data ecosystem, with a strong focus on building dependable, scalable, and efficient data solutions. The role will help shape engineering standards, strengthen platform governance, and support high-quality data delivery for enterprise analytics and emerging AI-driven use cases.</p><p><br></p><p>Responsibilities:</p><p>• Provide technical direction to engineering teams and guide the successful execution of complex data platform initiatives.</p><p>• Create and enhance robust data pipelines and reusable data products that support scalable analytics and reporting needs.</p><p>• Develop and refine cloud-based data solutions using Snowflake, dbt, Fivetran, and Azure services.</p><p>• Build automation-first, metadata-driven processing frameworks to improve consistency, maintainability, and operational efficiency.</p><p>• Design curated data structures using established modeling approaches such as Data Vault, Kimball, and dimensional modeling.</p><p>• Improve platform performance through tuning, cost management, and scalability planning across data workloads.</p><p>• Establish and reinforce best practices for data quality, governance, lineage tracking, observability, and CI/CD delivery.</p><p>• Support Azure-based integration, storage, compute, and DevOps capabilities required for reliable end-to-end data operations.</p><p>• Enable data foundations that can support advanced analytics, AI/ML initiatives, and modern analytical architectures.</p>
We are looking for a Data Engineer to help design and enhance data solutions that support reliable reporting and analytics in Salt Lake City, Utah. This role focuses on building scalable data pipelines, shaping well-structured warehouse models, and improving the quality and usability of enterprise data assets. The ideal candidate brings strong experience with SQL, Python, AWS technologies, and dimensional modeling principles grounded in the Kimball methodology.<br><br>Responsibilities:<br>• Build and maintain data pipelines that ingest, transform, and prepare information for downstream analytics and business use.<br>• Design warehouse structures using Kimball-based dimensional modeling practices to support clear, consistent reporting.<br>• Develop and optimize SQL- and Python-driven data workflows with an emphasis on scalability, performance, and maintainability.<br>• Partner with analysts, engineers, and business stakeholders to translate data needs into practical engineering solutions.<br>• Create and manage data transformation logic using dbt to improve testing, documentation, and deployment consistency.<br>• Support cloud-based data platforms in an AWS environment and contribute to ongoing improvements in data architecture.<br>• Monitor data quality and troubleshoot pipeline issues to ensure dependable delivery of curated datasets.<br>• Contribute to modern data engineering practices, including tools such as PySpark when needed for larger-scale processing.
<p>We are looking for a Data Engineer to build and enhance reporting and data solutions that help teams make informed business decisions across the organization. This role partners with groups such as asset management, acquisitions, accounting, and HR to translate business needs into scalable dashboards, reliable data pipelines, and actionable insights. Based in Los Angeles, California, the position is ideal for someone who combines strong technical depth with the ability to explain findings clearly to a range of stakeholders.</p><p><br></p><p>Responsibilities:</p><p>• Create and refine dashboards, reports, and automated data outputs using tools such as Python, Excel, and Power BI to support operational and strategic reporting needs.</p><p>• Examine large and varied datasets to uncover meaningful trends, performance indicators, and opportunities for improvement.</p><p>• Guide and support entry-level BI team members by reviewing work, sharing best practices, and contributing to their career growth.</p><p>• Partner with stakeholders across multiple business functions to define reporting goals, gather technical requirements, and deliver effective data solutions.</p><p>• Translate technical concepts and analytical results into clear recommendations for non-technical audiences.</p><p>• Contribute to cross-department initiatives that improve data availability, reporting consistency, and overall usability of business information.</p><p>• Develop and maintain queries, procedures, and data workflows to support extraction, transformation, and loading activities across reporting environments.</p><p>• Monitor data quality through validation checks, issue resolution, and routine audits to maintain accuracy and reliability.</p><p>• Administer BI platforms with attention to performance, access control, and system stability while assisting users with adoption and training.</p><p><br></p><p>For immediate consideration, apply now and direct message Reid Gormly on LinkedIn</p>
<p>We are looking for an experienced Data Engineer to jcreate and enhance dependable data platforms that support HR and enterprise analytics, partnering closely with analysts, engineering leads, and business stakeholders on site. The position focuses on building scalable pipelines, strengthening data quality, and enabling trusted insights that improve operational decision-making across the organization.</p><p><br></p><p>Responsibilities:</p><p>• Design, develop, and maintain scalable data pipelines that integrate information from files, APIs, databases, replicated sources, and streaming inputs.</p><p>• Build and support modern data environments across warehouses, data lakes, and lakehouse architectures to meet analytics and reporting needs.</p><p>• Partner with business analysts, HR stakeholders, and technical team members to translate data requirements into reliable engineering solutions.</p><p>• Improve data quality, lineage, and governance by applying metadata-driven practices and implementing controls that increase trust in enterprise datasets.</p><p>• Lead end-to-end delivery of data engineering initiatives, from solution design and development through testing, deployment, and operational support.</p><p>• Manage orchestration, scheduling, and monitoring of data workflows to ensure stable performance and timely delivery of critical datasets.</p><p>• Apply DevOps practices such as version control, automated testing, and CI/CD processes to increase deployment quality and team collaboration.</p><p>• Use Python, SQL, and cloud-based tools to automate data processing, optimize performance, and support scalable distributed workloads.</p><p>• Implement data protection measures, including masking, encryption, anonymization, and role-aware access design, especially for sensitive workforce information.</p><p>• Support curated analytical datasets and reporting solutions by collaborating with downstream users on trusted models and enterprise data products.</p>
<p>We are looking for a Data Engineer to support data-focused initiatives with a strong emphasis on controls, process clarity, and technical documentation. This is a Long-term Contract position expected to begin as a 3-4 month engagement at 40 hours per week, with remote work flexibility. The ideal candidate will help strengthen data workflows, improve reliability across engineering processes, and create well-organized documentation that supports ongoing delivery and compliance.</p><p><br></p><p>Responsibilities:</p><p>• Design, build, and maintain data pipelines that support reliable movement and transformation of information across platforms.</p><p>• Develop clear technical documentation, data process records, and control-related artifacts to improve transparency and audit readiness.</p><p>• Use Python, Apache Spark, and ETL frameworks to prepare, cleanse, and transform large datasets for downstream consumption.</p><p>• Work with Hadoop- and Kafka-based environments to support scalable data processing and streaming or batch integration needs.</p><p>• Review existing data workflows to identify gaps in controls, consistency, and documentation quality, then recommend practical improvements.</p><p>• Collaborate with cross-functional stakeholders to clarify data requirements, align engineering deliverables, and support operational continuity.</p><p>• Monitor pipeline performance and troubleshoot data issues to maintain dependable processing and accurate outputs.</p>
We are looking for a Data Engineer to support a short-term Contract engagement focused on assessing and strengthening OpenLink security role design for a recently acquired business. This position will play a key role in reviewing current configurations, identifying gaps in segregation of duties, and helping shape a more effective access model. The role is based in Cincinnati, Ohio, with flexibility for remote or hybrid work depending on experience and project needs.<br><br>Responsibilities:<br>• Evaluate the existing OpenLink security framework and determine how well current role assignments support appropriate access controls.<br>• Recommend and help design an improved security role structure that aligns with segregation-of-duties expectations across the environment.<br>• Configure and refine OpenLink settings to support a secure, scalable, and well-governed access model.<br>• Partner with project stakeholders to document findings, explain risk areas, and outline practical remediation options.<br>• Support analysis related to the acquired company’s OpenLink setup and identify where adjustments are needed for consistency and control.<br>• Contribute technical expertise during project discussions, providing guidance on role configuration best practices and implementation considerations.<br>• Use data engineering tools and scripting capabilities to assist with analysis, validation, and supporting technical tasks where applicable.
We are looking for a Data Engineer to join our team in Jacksonville, Florida and help shape scalable, enterprise-ready analytics solutions. In this role, you will turn complex business needs into well-structured data models, high-performing pipelines, and actionable reporting assets that support informed decision-making. The ideal candidate brings deep experience with modern data platforms, strong technical leadership, and the ability to guide best practices for analytics, governance, and data usability across the organization.<br><br>Responsibilities:<br>• Design and maintain scalable data pipelines and transformation workflows using tools such as Python, Apache Spark, Hadoop, Kafka, and ETL frameworks.<br>• Build and optimize enterprise semantic models that support consistent metrics, reusable analytics assets, and reliable reporting across multiple business areas.<br>• Partner with business and technical stakeholders to convert complex requirements into practical data solutions, dashboards, and analytical datasets.<br>• Develop and support analytics solutions within modern cloud and hybrid environments, with a strong focus on Microsoft Power BI, Microsoft Fabric, and Azure Synapse Analytics.<br>• Improve data quality, model performance, and platform reliability through testing, validation, tuning, and adherence to established governance standards.<br>• Provide technical guidance to team members by sharing best practices in data modeling, visualization, and scalable analytics design.<br>• Evaluate and incorporate AI-enabled analytics capabilities and automation opportunities while ensuring outputs align with business needs and quality expectations.<br>• Communicate technical concepts and analytical insights clearly to a range of audiences, including leadership, to support strategic decisions.
We are looking for a Data Engineer to help build reliable data solutions that support reporting, analytics, and day-to-day business decisions in Princeton, New Jersey. This position focuses on creating scalable data flows, improving platform performance, and organizing data for efficient access across teams. The ideal candidate brings strong technical depth in pipeline development, database technologies, and cloud-based data environments.<br><br>Responsibilities:<br>• Build, enhance, and support scalable ETL workflows that move and transform data from multiple sources into trusted analytical platforms.<br>• Create and refine data models, storage structures, and warehouse solutions to improve accessibility, efficiency, and long-term maintainability.<br>• Monitor data processes to identify issues, strengthen reliability, and maintain high standards for accuracy, consistency, and performance.<br>• Partner with analytics, engineering, and business stakeholders to understand data needs and deliver practical data solutions.<br>• Optimize SQL Server and related data systems to support efficient querying, integration, and operational stability.<br>• Implement and maintain orchestration processes using tools such as Airflow or comparable workflow technologies.<br>• Contribute to cloud-based data infrastructure initiatives across platforms such as Azure and other enterprise cloud environments.
<p>Robert Half is seeking a <strong>Contract Data Engineer</strong> to support our client’s data and analytics initiatives. In this role, you will be responsible for designing, building, and maintaining scalable data pipelines and infrastructure that enable efficient data ingestion, transformation, and delivery. The ideal candidate has strong experience working with modern data platforms, cloud environments, and large-scale datasets.</p><p><br></p><p><strong>Key Responsibilities:</strong></p><ul><li><strong>Data Pipeline Development:</strong> Design, build, and maintain scalable ETL / ELT pipelines to ingest, transform, and deliver data from multiple sources.</li><li><strong>Data Architecture:</strong> Develop and optimize data models, schemas, and warehouse structures to support analytics, reporting, and business intelligence needs.</li><li><strong>Cloud Data Platforms:</strong> Work within cloud environments such as <strong>AWS, Azure, or GCP</strong> to deploy and manage data solutions.</li><li><strong>Data Warehousing:</strong> Design and support enterprise data warehouses using platforms such as <strong>Snowflake, Redshift, BigQuery, or Azure Synapse</strong>.</li><li><strong>Big Data Processing:</strong> Develop solutions using big data technologies such as <strong>Spark, Databricks, Kafka, and Hadoop</strong> when required.</li><li><strong>Performance Optimization:</strong> Tune queries, pipelines, and storage solutions for performance, scalability, and cost efficiency.</li><li><strong>Data Quality & Reliability:</strong> Implement monitoring, validation, and alerting processes to ensure data accuracy, integrity, and availability.</li><li><strong>Collaboration:</strong> Work closely with Data Analysts, Data Scientists, Software Engineers, and business stakeholders to understand requirements and deliver data solutions.</li><li><strong>Documentation:</strong> Maintain detailed documentation for pipelines, data flows, and system architecture.</li></ul><p><br></p>
<p>We are looking for a Data Engineer to join an immediate contract opportunity in Woodbury, Minnesota. In this role, you will help advance a customer-focused analytics platform by creating reliable data solutions that support reporting, APIs, and interactive insights. You will work closely with technical and business partners to shape scalable data structures and deliver high-quality information products in a collaborative environment.</p><p><br></p><p>Responsibilities:</p><p>• Create and support robust data pipelines that move and prepare information for analytics and downstream applications.</p><p>• Build transformation workflows using dbt and optimize processing logic with Python, Spark SQL, and PySpark.</p><p>• Coordinate scheduled and dependency-driven data jobs with Apache Airflow to ensure consistent delivery.</p><p>• Ingest and manage data within an on-premises environment, maintaining efficiency, quality, and availability.</p><p>• Develop data services and API-ready outputs so customers can access information through external BI and analytics tools.</p><p>• Contribute to semantic and visualization layers, including tools such as Cube.dev or similar platforms, to improve analytics usability.</p><p>• Partner with application and dashboard developers to align data structures with customer-facing reporting needs.</p><p>• Work with stakeholders across product, business, and engineering teams to define solutions that support platform goals and user expectations.</p><p>• Apply modern development practices and AI-assisted tools where appropriate to improve productivity and accelerate delivery.</p>
We are looking for a Data Engineer to build and enhance scalable data solutions that support analytics and business decision-making in Jacksonville, Florida. This role focuses on designing reliable warehouse structures, developing efficient data pipelines, and improving data quality across enterprise platforms. The ideal candidate brings strong technical depth in modern data engineering practices and is comfortable partnering with cross-functional teams to deliver well-governed, high-performing data assets.<br><br>Responsibilities:<br>• Design and maintain enterprise data warehouse solutions using dimensional modeling techniques that support reporting, analytics, and long-term scalability.<br>• Develop, orchestrate, and optimize ETL and ELT workflows for batch and near real-time data movement using modern pipeline and scheduling tools.<br>• Build robust data architectures across cloud-based platforms while balancing performance, resilience, and cost efficiency.<br>• Troubleshoot pipeline failures, data inconsistencies, and performance bottlenecks, then implement practical fixes that improve reliability and throughput.<br>• Apply governance standards by supporting data quality controls, metadata practices, lineage visibility, and role-based access management.<br>• Partner with business and technical stakeholders to translate data needs into well-structured solutions and provide clear updates on progress, risks, and delivery timelines.<br>• Create efficient code for data transformation and aggregation using Python and advanced query development techniques.<br>• Integrate data from databases, APIs, streaming platforms, and external sources to support a broad range of analytical use cases.<br>• Mentor team members and contribute ideas that streamline processes, reduce friction, and strengthen engineering best practices.
We are looking for a Data Engineer to help maintain and improve a mission-driven technology environment that supports essential nonprofit operations in Battle Creek, Michigan. This position blends application support, database engineering, and systems integration work, making it ideal for someone who enjoys solving technical problems across multiple platforms. The role works closely with internal teams and external partners to keep business systems reliable, data accurate, and reporting processes running smoothly.<br><br>Responsibilities:<br>• Maintain and resolve issues across core business applications, including Dynamics 365 Business Central, Microsoft 365, SharePoint, Power BI, procurement tools, workforce systems, and other connected platforms.<br>• Administer Microsoft SQL Server environments by monitoring system health, tuning performance, managing security access, and overseeing backup, recovery, upgrade, and capacity planning activities.<br>• Build, refine, and troubleshoot SQL queries to support operational needs while identifying and correcting data consistency, accuracy, and reconciliation problems between systems.<br>• Develop and support integrations, APIs, ETL processes, Azure Data Factory workflows, scheduled data exchanges, and SFTP-based transfers to ensure dependable movement of information across platforms.<br>• Investigate reporting and data warehouse issues by resolving failed loads, refresh interruptions, and mismatches between source systems and business intelligence outputs.<br>• Contribute to software rollouts and system enhancements through testing, data conversion support, deployment activities, post-launch issue resolution, and production stabilization efforts.<br>• Partner with software vendors and external service providers to diagnose complex technical challenges and drive incidents through to completion.<br>• Create and maintain clear technical documentation for applications, databases, integrations, and data flows while sharing knowledge with teammates to strengthen team coverage.<br>• Support both strategic engineering work and day-to-day technical tasks within a collaborative IT team, adapting to changing priorities as needed.
We are looking for a Data Engineer to join a fast-paced IT consulting environment in Atlanta, Georgia. In this role, you will design and optimize modern data solutions that support analytics, machine learning, and business decision-making across a variety of client initiatives. The ideal candidate brings strong technical depth in cloud-based data engineering along with a practical, solution-oriented mindset. This position is well suited for someone who enjoys turning complex data challenges into scalable and reliable platforms.<br><br>Responsibilities:<br>• Build and maintain robust data pipelines that move, transform, and prepare information for reporting, analytics, and operational use.<br>• Design end-to-end data solutions within Azure-based environments, using the right services and frameworks to support performance, reliability, and scale.<br>• Develop engineering workflows with Python and PySpark to process both structured datasets and more complex unstructured sources.<br>• Create and support data architecture components in Microsoft Fabric, Databricks, and related platforms to enable efficient data access and delivery.<br>• Implement pipeline orchestration and workflow automation through Databricks tools to streamline recurring data operations.<br>• Support machine learning initiatives by preparing high-quality datasets and building pipelines that feed model development and deployment processes.<br>• Apply sound data management practices to ensure consistency, usability, and governance across data assets.<br>• Work within Azure DevOps-driven delivery environments to contribute to version control, deployment processes, and collaborative engineering practices.<br>• Partner with stakeholders to understand business objectives, translate requirements into technical solutions, and deliver strong client-focused outcomes.
We are looking for a Data Engineer to help shape and expand a cloud-focused data environment that supports analytics, operational reporting, automation, and emerging AI use cases. Based in Brookfield, Wisconsin, this position works across technical and business teams to deliver dependable data solutions that improve access, accuracy, and usability. The role is ideal for someone who thrives on translating complex data needs into scalable engineering outcomes and values collaboration, problem-solving, and continuous improvement.<br><br>Responsibilities:<br>• Design, build, and maintain scalable data pipelines that move and transform information for analytics, reporting, and operational needs.<br>• Partner with business stakeholders, analysts, software developers, and leaders to understand data requirements and turn them into reliable engineering solutions.<br>• Develop and refine data models and platform architecture to support performance, flexibility, and long-term growth.<br>• Implement ETL processes that integrate data from multiple sources while improving consistency, completeness, and accessibility.<br>• Use Python and distributed data technologies such as Apache Spark and Hadoop to process large and complex datasets efficiently.<br>• Support streaming and event-driven data workflows using tools such as Apache Kafka where real-time data delivery is needed.<br>• Monitor data quality, troubleshoot pipeline issues, and optimize workflows to ensure dependable delivery and strong system performance.<br>• Contribute to ongoing enhancements of the data platform by identifying opportunities to improve scalability, automation, and engineering standards.
We are looking for an experienced Data Engineer to join a construction and contractor-focused organization in Appleton, Wisconsin. This contract opportunity with potential for a permanent role is ideal for a senior-level candidate who enjoys building scalable cloud-based data platforms, working hands-on with Python and notebook-driven development, and applying AI-enabled tools to create practical business solutions. The role will focus on designing modern data lake capabilities, improving data movement and transformation processes, and partnering with stakeholders to deliver reliable analytics infrastructure.<br><br>Responsibilities:<br>• Design, build, and enhance modern data lake architecture in Google Cloud Platform to support scalable and efficient data operations.<br>• Develop robust data pipelines using Python, SQL, Spark, and ETL frameworks to ingest, transform, and prepare data from multiple sources.<br>• Create and maintain notebook-based solutions that demonstrate clear technical approaches, reusable logic, and well-documented project outcomes.<br>• Integrate large-scale data processing technologies such as Hadoop and Kafka to support high-volume and streaming data workloads.<br>• Collaborate with cross-functional teams to translate business needs into data engineering solutions that improve reporting, analytics, and operational decision-making.<br>• Apply AI-driven tools and approaches to accelerate development, improve solution quality, and deliver innovative customer-focused outcomes.<br>• Support cloud data environments that may include Azure Data Lake and related platforms as part of broader enterprise data initiatives.<br>• Contribute to data platform improvements, including work connected to enterprise tool adoption or internal platform changes when needed.
<p>We are looking for a Data Engineer to help build and maintain reliable data solutions for a client. This position focuses on moving, transforming, and validating data from multiple sources to support reporting, analytics, and operational needs. The ideal candidate will be comfortable working with modern cloud data platforms, collaborating with cross-functional teams, and improving data processes for accuracy, consistency, and timely delivery.</p><p><br></p><p>Responsibilities:</p><p>• Design, develop, and maintain data pipelines that ingest information from APIs, files, network sources, and other internal or external systems.</p><p>• Build and enhance automated data workflows using Snowflake, Azure Data Factory, Python, and SQL to support reporting and analytics needs.</p><p>• Apply business rules to transform raw data into structured, usable datasets for analysts, stakeholders, and downstream applications.</p><p>• Partner with business users, analysts, developers, and project teams to gather requirements and deliver data solutions within an agile environment.</p><p>• Monitor data quality by validating, cleansing, and reconciling datasets to ensure dependable and consistent information availability.</p><p>• Troubleshoot pipeline failures, data inconsistencies, and integration issues, then implement fixes to improve system stability.</p><p>• Maintain clear documentation for data warehouse configurations, workflow logic, and processing standards.</p><p>• Manage code and workflow changes through version control practices to support traceability and controlled deployment.</p><p>• Improve the timeliness and efficiency of data delivery for internal teams and third-party data consumers by identifying process enhancements.</p>
We are looking for a Data Engineer to take ownership of a growing enterprise data platform. This role is best suited for a highly capable, hands-on individual who can build, optimize, and support modern data solutions while working closely with business and technical stakeholders. The position offers the opportunity to shape data architecture, improve data accessibility, and contribute to a scalable analytics environment. This is an onsite role, with three days per week in the office.<br><br>Responsibilities:<br>• Design, build, and maintain scalable data pipelines that support enterprise reporting, analytics, and operational needs.<br>• Develop and enhance data integration workflows using Microsoft Fabric or Azure Data Factory to move and transform data efficiently.<br>• Create and refine data models and architecture standards to improve consistency, performance, and long-term usability across platforms.<br>• Write production-quality Python code to automate data processing, validation, and orchestration tasks.<br>• Partner with cross-functional teams to understand business requirements and translate them into practical data engineering solutions.<br>• Monitor data platform performance, troubleshoot issues, and implement improvements that strengthen reliability and maintainability.<br>• Work with large-scale data technologies such as Spark, Hadoop, Kafka, and ETL frameworks to support evolving data initiatives.<br>• Contribute to the expansion of the data function by documenting processes and, over time, providing guidance to team members as needed.
Position: Data Engineer<br>Location: Oskaloosa, IA / Des Moines, IA -- Onsite<br>Salary: $100,000 - $120,000 base + exceptional benefits<br><br>*** For immediate and confidential consideration, please APPLY and EMAIL YOUR RESUME to MEREDITH CARLE . My email can be found on my LinkedIn page. ***<br><br>Data Engineer<br>Shape the Future of Enterprise Analytics, AI & Data Innovation<br>Are you the type of data professional who sees a business problem and immediately starts thinking about how to model, engineer, and deliver the right solution?<br>A highly successful, technology-driven organization is seeking a Data Engineer to help build the foundation for enterprise analytics, business intelligence, governance, and next-generation AI initiatives. This is an opportunity to make a visible impact across the business while working alongside a collaborative team of data professionals who are passionate about solving complex challenges.<br>This role is ideal for someone who enjoys being hands-on, partnering with the business, and building modern data solutions that drive meaningful outcomes.<br>What You'll Do<br> • Design and develop scalable data models, semantic layers, and enterprise data solutions<br> • Build trusted data structures that support analytics, reporting, AI, and business intelligence initiatives<br> • Develop and optimize cloud-based data pipelines and integrations<br> • Improve data governance, lineage, metadata management, and observability practices<br> • Create automated data quality and validation frameworks<br> • Implement CI/CD processes and modern DataOps best practices<br> • Optimize SQL performance across warehouses, lakehouses, and reporting environments<br> • Partner with analysts and business stakeholders to transform complex problems into actionable solutions<br> • Contribute to technical standards, mentoring, documentation, and architectural best practices<br>What We're Looking For<br>Core Qualifications<br> • Strong experience with data modeling and semantic modeling<br> • Hands-on experience with Microsoft Fabric, Azure, and Power BI<br> • Advanced SQL development and performance optimization skills<br> • Experience with Git, CI/CD, and modern data engineering practices<br> • Ability to translate business requirements into scalable technical solutions<br> • Experience developing enterprise data pipelines and analytics platforms<br> • A plus if you have data governance, data warehouse, data lake and or DBT experience.<br><br>*** For immediate and confidential consideration, please APPLY and EMAIL YOUR RESUME to MEREDITH CARLE . My email can be found on my LinkedIn page. Also, you may contact me at 515-303-4654. Or one click apply on our Robert Half website. No third party inquiries please. Our client cannot provide sponsorship and cannot hire C2C. ***
We are looking for a Data Engineer to join a Financial Services team in Plano, Texas on a contract basis with the potential for a permanent role. This role is focused on designing and delivering reliable data pipelines in a cloud-first environment, with Snowflake serving as a central platform for analytics and data consumption. The position offers a balanced mix of new development and targeted optimization, with an emphasis on improving data quality, operational visibility, and scalable processing capabilities.<br><br>Responsibilities:<br>• Design, build, and deploy end-to-end data pipelines with Snowflake as a primary data platform.<br>• Create new ingestion and transformation workflows while resolving issues affecting existing pipeline performance and reliability.<br>• Support streaming data integration using Apache Kafka to enable timely and scalable data movement.<br>• Strengthen observability across data workflows by improving monitoring, alerting, and pipeline transparency.<br>• Enhance data quality practices through validation, testing, and proactive issue identification.<br>• Modernize data architecture by reducing dependency on legacy processes and addressing technical debt.<br>• Contribute to engineering standards by applying disciplined development practices, code quality measures, and repeatable delivery methods.<br>• Help expand CI/CD and testing capabilities by promoting more consistent automation across build and release activities.<br>• Use AI-assisted development tools to accelerate coding, testing, and documentation where appropriate.
<p>A Manufacturing/ distribution company is looking for a Data Engineer with 3 + years of experience to join a dynamic team in Oklahoma City, Oklahoma. In this role, you will play a crucial part in designing and maintaining data infrastructure to support analytics and decision-making processes. You will be a key contributor in developing, optimizing, and maintaining the data infrastructure that supports analytics and business intelligence initiatives, and data driven decision-making using Snowflake, Matillion, and other tools. Position will be in-office to work closely with the team. You must live in the Oklahoma City area. Client is unable to sponsor. No 3rd parties please.</p><p><br></p><p>Responsibilities:</p><p><br></p><p>• Design, develop, and maintain scalable data pipelines to support data integration and real-time processing.</p><p>• Implement and manage data warehouse solutions, with a strong focus on Snowflake architecture and optimization.</p><p>• Write efficient and effective scripts and tools using Python to automate workflows and enhance data processing capabilities.</p><p>• Work with SQL Server to design, query, and optimize relational databases in support of analytics and reporting needs.</p><p>• Monitor and troubleshoot data pipelines, resolving any performance or reliability issues.</p><p>• Ensure data quality, governance, and integrity by implementing and enforcing best prac</p>
We are looking for a Data Engineer to join our team in Texas. In this role, you will create and enhance modern cloud data platforms that power reporting, analytics, and intelligent business solutions. The position is ideal for a hands-on individual who excels at building scalable pipelines, improving data performance, and partnering with technical and business teams to deliver reliable data products.<br><br>Responsibilities:<br>• Create and maintain cloud-based data solutions on Azure using services such as Databricks, Synapse Analytics, Data Factory, and related platform tools.<br>• Build resilient data pipelines and integration workflows that support enterprise analytics, reporting, and business intelligence across large and complex datasets.<br>• Architect and implement lakehouse and warehouse environments, including layered data models that organize raw, refined, and business-ready data.<br>• Develop reusable notebooks and processing frameworks with Python, PySpark, Spark, and Scala to support scalable engineering patterns.<br>• Tune and troubleshoot data workloads to improve speed, stability, scalability, and overall cost efficiency in production environments.<br>• Deliver end-to-end data solutions by handling design, development, testing, deployment, documentation, and ongoing operational support.<br>• Apply source control, DevOps practices, and automated release processes to enable consistent and secure deployments.<br>• Partner with stakeholders, engineers, and leadership to convert business needs into practical technical designs and data solutions.<br>• Support AI and machine learning initiatives through data preparation, feature development, curated datasets, and platform capabilities for advanced analytics.<br>• Investigate production issues, evaluate new technologies, and recommend improvements that strengthen reliability, efficiency, and business value.
We are looking for a Data Engineer to help build and maintain scalable data solutions that support critical business operations within the brokerage industry. This role is based in Chicago, Illinois, and focuses on designing reliable data pipelines, improving data accessibility, and enabling efficient processing across large datasets. The ideal candidate brings strong technical expertise in modern data engineering tools and enjoys working in a fast-paced environment where data quality, performance, and consistency are essential.<br><br>Responsibilities:<br>• Design, develop, and optimize data pipelines that support ingestion, transformation, and delivery of large-scale datasets.<br>• Build and maintain ETL workflows to ensure accurate, timely, and dependable movement of data across platforms.<br>• Use Python and Apache Spark to process complex data efficiently and improve overall pipeline performance.<br>• Work with Apache Hadoop technologies to manage distributed data storage and computation for high-volume workloads.<br>• Implement streaming and messaging solutions with Apache Kafka to support near-real-time data integration needs.<br>• Partner with cross-functional teams to understand data requirements and translate business needs into technical solutions.<br>• Monitor data processes, troubleshoot issues, and resolve bottlenecks to maintain system reliability and data integrity.<br>• Contribute to enhancements involving data platform changes or internal process updates as part of ongoing engineering initiatives.
<p>We are looking for a Data Platform Engineer to join a 4-month contract opportunity based in Norman, Oklahoma. This role owns the storage, retention and pipeline-correctness workstream. This is data engineering, not cloud </p><p>infrastructure.</p><p><br></p><p>What they will actually do</p><p>▪ Own the storage and pipeline backlog across the ingestion and processing repositories</p><p>▪ Event ordering and bitemporal modelling: separating event time from ingestion time, deterministic replay</p><p>▪ Atomic snapshot publication with schema admission and rollback</p><p>▪ Design the historical layer on object storage so it can be queried economically and answer as-of </p><p>questions correctly — file format, partitioning, compaction, and whether the canonical layer moves </p><p>onto a managed table format</p><p>▪ Reconcile the operational database and the historical store so a point-in-time question returns one </p><p>answer rather than two</p><p>▪ Evidence immutability and retention: object-lock semantics, preventing overwrite of stored evidence, </p><p>validated recovery paths</p><p>▪ Pipeline durability: idempotent runs, completeness receipts, restore testing</p><p>▪ Support production cutover in month 4 — this seat does not roll off early</p>
We are looking for a Data Engineer to join a growing team and contribute to the delivery of reliable, analytics-ready data solutions. This contract opportunity with potential for a permanent role is ideal for someone who enjoys building scalable data pipelines, improving data models, and partnering with technical and business stakeholders to support reporting, self-service analytics, and data science. The role offers the chance to work hands-on with Databricks, Python, PySpark, SQL, and modern data engineering practices in a collaborative environment focused on quality and performance.<br><br>Responsibilities:<br>• Build, maintain, and enhance data pipelines that support dependable data availability for analytics and reporting needs.<br>• Collaborate with data engineering leaders to troubleshoot defects, resolve pipeline issues, and improve overall platform stability.<br>• Develop transformation logic using Python, PySpark, SQL, and Databricks to prepare clean, usable datasets for downstream consumers.<br>• Design and refine data models that improve usability, consistency, and performance across reporting and analytical workloads.<br>• Apply layered data architecture principles, including Bronze, Silver, and Gold structures, to organize and manage data effectively.<br>• Establish and follow engineering standards for validation, testing, monitoring, and documentation to strengthen data quality and maintainability.<br>• Optimize processing and query performance to support efficient data delivery at scale.<br>• Work with business and technical partners to translate data needs into practical engineering solutions that support trusted insights.
We are looking for an experienced Database Technology Manager to oversee the stability, security, and performance of enterprise database environments in Tempe, Arizona. This role combines hands-on database administration with team leadership, requiring someone who can guide technical staff, improve operational standards, and communicate clearly with both technical and non-technical stakeholders. The ideal candidate brings strong Microsoft SQL Server expertise, a disciplined approach to backup and recovery planning, and the ability to support reliable database operations in a regulated setting.<br><br>Responsibilities:<br>• Lead the administration and day-to-day support of production Microsoft SQL Server environments, ensuring high availability, reliability, and consistent performance.<br>• Supervise and mentor technical team members, establish operational standards, and review database-related work for quality and accuracy.<br>• Manage core SQL Server services and features, including instance setup, Always On availability groups, backup and restore processes, SQL Server Agent, and Database Mail.<br>• Develop, maintain, and validate backup and disaster recovery strategies through regular testing and documented recovery procedures.<br>• Analyze database performance issues using execution plans, wait statistics, and tuning techniques to improve efficiency and system responsiveness.<br>• Create and maintain PowerShell-based automation to streamline administrative tasks and reduce manual effort.<br>• Oversee database security controls, permissions, and compliance practices within an audited or regulated environment.<br>• Produce clear technical documentation such as runbooks, incident summaries, and architecture recommendations for a broad audience.<br>• Support upgrade and migration activities across database versions when needed, while minimizing operational disruption.<br>• Participate in on-call support rotations and perform after-hours maintenance to sustain system availability.